Fred Sonnenwald - Research Assoicate

Profile

Fred Sonnenwald graduated with a MEng in Civil Engineering from the University of Sheffield in 2010. He stayed on and completed his PhD on "Identifying the residence time distributions of urban drainage structures from solute transport data using maximum entropy deconvolution" in 2014.

Fred's research has broadly covered two main subjects. The first, based off his PhD work, is on the identification and interpretation of residence time distributions, or RTDs. An RTD is the distribution of times a particle of water may reside in a system. It forms a non-parametric model that fully describes the hydraulic/mixing processes occurring without any a-priori assumptions. Researchers can deconvolve dye tracing data obtained experimentally to obtain an RTD, and use the resulting RTD to gain new insight into the hydrodynamics of the measured system. This is of particular interest for complex hydraulic structures, such as manholes, where detailed laboratory measurements are infeasible due to the scale and complexity of the structure.

The second area of Fred's research is environmental fluid mechanics. Fred has worked for the last four years on developing computational fluid dynamics (CFD) based approaches to describing mixing occurring within vegetation. He has coupled this with full-scale models of vegetated stormwater ponds to gain new insights into the pond design process and the effectiveness of ponds as constructed treatment devices. This work will inform future design guidance for vegetated stormwater ponds to ensure consistent treatment.